A Systematic Literature Review of Automated Feedback Generation for Programming Exercises

Formative feedback, aimed at helping students to improve their work, is an important factor in learning. Many tools that offer programming exercises provide automated feedback on student solutions. We have performed a systematic literature review to find out what kind of feedback is provided, which...

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Bibliographic Details
Published inACM transactions on computing education Vol. 19; no. 1
Main Authors Keuning, Hieke, Jeuring, Johan, Heeren, Bastiaan
Format Journal Article
LanguageEnglish
Published Association for Computing Machinery 01.01.2019
Subjects
Classification
Coding
Computer Assisted Instruction
Computer Science Education
Computer Software
Error Correction
Feedback (Response)
Intelligent Tutoring Systems
Programming
Teaching Methods
Validity
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Summary:Formative feedback, aimed at helping students to improve their work, is an important factor in learning. Many tools that offer programming exercises provide automated feedback on student solutions. We have performed a systematic literature review to find out what kind of feedback is provided, which techniques are used to generate the feedback, how adaptable the feedback is, and how these tools are evaluated. We have designed a labelling to classify the tools, and use Narciss' feedback content categories to classify feedback messages. We report on the results of coding a total of 101 tools. We have found that feedback mostly focuses on identifying mistakes and less on fixing problems and taking a next step. Furthermore, teachers cannot easily adapt tools to their own needs. However, the diversity of feedback types has increased over the past decades and new techniques are being applied to generate feedback that is increasingly helpful for students.
ISSN:1946-6226
1946-6226
DOI:10.1145/3231711